Abstract
This paper presents a predictor which minimizes the cost function of the prediction error in a minimax sense, yielding minimization of the peaks of the prediction error spectrum, rather than its integral on the unit circle. This predictor is then used for the derivation of a predictive minimax control law. This one degree of freedom control law minimizes the peaks of a generalized cost function in the frequency domain. The predictor and control algorithms are derived via embedding of the minimax problem within an LQ problem using polynomial methods.
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